conceptual-modelinglisted

Use when translating messy business requirements, stakeholder language, or early product ideas into an implementation-neutral domain model before database schemas, API endpoints, or DDD aggregates are named. Covers entities, attributes, named relationships, cardinality, identity criteria, specialization/generalization, aggregation/composition, reification, abstraction-level control, stakeholder validation, and modeling anti-patterns. Do NOT use for database ER diagrams with keys and normalization, formal ontology axioms with OWL/RDFS, or DDD tactical design; use those dedicated skills instead. Do NOT use for give me the physical table design with PKs, FKs, and normalization forms. Do NOT use for turn this model into SQL migrations and index definitions. Do NOT use for I need OWL class axioms and reasoning constraints for these concepts. Do NOT use for build the DDD aggregate boundaries and anti-corruption layer. Do NOT use for what hypernymy or meronymy labels apply between these two terms.
jacob-balslev/skill-graph · ★ 0 · AI & Automation · score 68

Install: claude install-skill jacob-balslev/skill-graph

# Conceptual Modeling ## Coverage Conceptual modeling translates real-world domain language into a structured, stakeholder-readable model before implementation details are allowed to enter. It covers: - Entity discovery: distinguishable things the domain tracks, with identity criteria for what makes two instances the same. - Attribute placement: properties that describe one entity, derived values, multi-valued attributes, and signals that an attribute is actually a missing entity. - Relationship modeling: named relationships, role labels, cardinality, optionality, direction, aggregation, composition, association, dependency, and relationship reification. - Specialization and generalization: subtype/supertype modeling with disjoint versus overlapping and total versus partial constraints. - Abstraction-level control: keeping conceptual models above logical schemas, physical storage, APIs, ontology axioms, and DDD tactical design. - Stakeholder validation: scenario walk-throughs, negative testing, terminology audits, and conflict resolution when different stakeholders use different concepts. - Anti-pattern detection: implementation leakage, missing entity, god entity, phantom relationship, premature normalization, attribute-as-entity, unnamed relationship, and over-formalization. ## Philosophy Every software system is a model of a domain. If the model is wrong, correct code faithfully automates the wrong understanding. Conceptual modeling exists to make the model explicit w